According to several industry estimates, the global humanoid robot market could reach between $30 billion and $60 billion by 2035, with annual growth exceeding 35%. Yet today, less than 1% of industrial companies use humanoids in real production environments. The gap between potential and adoption is telling.

From Technical Demonstration to Industrial Reality

Recent advances in robotics, driven by artificial intelligence and imitation learning, have made it possible to cross a major threshold. In 2025, several prototypes capable of performing picking or assembly tasks were unveiled. In 2026, some manufacturers are announcing tests involving fleets of 10 to 100 robots in controlled environments.

But those figures remain marginal. For comparison, a single automotive plant can deploy more than 1,000 traditional industrial robots.

The transition toward mass adoption involves challenges of a completely different nature:

• System standardization
• Large-scale maintenance
• Software interoperability
• Total cost of ownership (TCO)

Today, the cost of a humanoid robot still ranges between $50,000 and $150,000, which significantly limits large-scale deployment.

The real challenge is no longer
making a robot walk, but making
it work at scale.

We are no longer selling machines,
but ecosystems where hardware is
only the visible part of the data layer.

A Redefinition of the Robotics Model

The traditional robotics framework is evolving toward a systemic approach. In 2026, the most advanced players are no longer selling robots alone, but complete solutions integrating:

• Hardware
• Software
• Infrastructure
• Services
• Data

There is a clear convergence with SaaS models, where value shifts toward operations and data management.

Humanoid robotics is entering a new phase. After the era of technological innovation (2015–2025), the decade 2025–2035 will be defined by large-scale deployment.

The bottleneck has shifted toward infrastructure, regulation, and market integration. The companies that will dominate this market will not simply be those designing the most advanced robots, but those capable of deploying them at scale in real-world environments.

The next revolution will not be technological. It will be operational.

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A technical comparison at the heart of processors and protocols.

Rockwell Automation: The Strength of “Logix” and EtherNet/IP

The Milwaukee giant is built on one philosophy: The Connected Enterprise. Rockwell’s architecture is centered on the Logix controller family (ControlLogix and CompactLogix) and the Studio 5000 development environment.

Technical DNA:

Core protocol: Everything is built around EtherNet/IP. Unlike others that rely on proprietary layers, Rockwell uses CIP (Common Industrial Protocol) over standard Ethernet. This makes integration with enterprise IT layers easier, with Cisco as a long-time partner.

Programming philosophy: The approach is tag-based. Engineers do not manipulate raw memory addresses, but named variables directly at the firmware level.

Strengths: Exceptional native integration between drives (PowerFlex), HMIs (FactoryTalk), and PLCs. It is the “Apple” of industry: a closed ecosystem, but one that runs with remarkable smoothness.

Robot Magazine verdict: Ideal for large-scale process projects and heavy industry, where maintenance must be simplified as much as possible.

Automation is no longer a
hardware choice, it is a
20-year strategy.

Schneider Electric: EcoStruxure and Universal Openness

Schneider Electric has undergone a spectacular transformation, moving from a hardware manufacturer to a leader in industrial software. Its EcoStruxure architecture positions itself as the most open on the market, relying heavily on international standards.

Technical DNA:

Software convergence: With the acquisition of AVEVA, Schneider offers full digital continuity, from sensor to cloud. The PLC (M580 or M262) is no longer more than a node in a broader information network.

IEC 61499 innovation: Schneider is at the forefront of the IEC 61499 standard through EcoStruxure Automation Expert. Unlike the classic IEC 61131 standard, which is cyclical, IEC 61499 is event-driven and allows intelligence to be distributed: a block of code can run equally well in a speed drive or in the central PLC.

Strengths: Unmatched energy management. It is the architecture of choice for smart factories seeking to correlate power consumption with productivity.

Robot Magazine verdict: The most mature solution for those who want to break down silos between pure automation and data management (Big Data/AI).

Beckhoff: The PC-Based Revolution and the Power of EtherCAT

While Rockwell and Schneider are evolving the traditional PLC, German company Beckhoff has essentially eliminated it and replaced it with an industrial PC (IPC).

Technical DNA:

TwinCAT: The core of the system. It is a software platform that transforms a Windows kernel into a hard real-time operating system. It uses the computing power of Intel and AMD processors to drive ultra-complex machines.

Master of EtherCAT: Beckhoff invented EtherCAT, the fastest fieldbus in the world. Unlike EtherNet/IP, which sends individual packets, EtherCAT reads and writes data on the fly within a single frame that passes through all modules. The result: cycle times below 100 microseconds.

IT/OT integration: Beckhoff pioneered the use of C++ and C# directly in industrial control, alongside traditional Ladder Logic and Structured Text.

Robot Magazine verdict: The ultimate weapon for precision robotics, high-speed packaging, and special-purpose machines requiring intensive mathematical computation.

Topology Comparison: A Clash of Cultures

In Industry 4.0, software is
the new master of the
forge.

In-Depth Analysis: The Performance Duel

Motion control

In robotics, Beckhoff remains one step ahead thanks to EtherCAT. The synchronization of hundreds of axes happens with no perceptible latency. However, Rockwell has responded with its intelligent transport technologies, such as iTRAK, offering simplified mechanical and electronic integration for next-generation conveyor systems. Schneider, for its part, stands out with its Lexium range and its ability to integrate Delta or articulated robots through rich software libraries.

Cybersecurity: a critical challenge

Rockwell and Schneider have both adopted IEC 62443-4-2 certification, integrating security chips such as Secure Boot directly into their CPUs. Schneider emphasizes traffic transparency through integrated firewalls, while Rockwell focuses on granular access-right management via FactoryTalk Security. Beckhoff, by using Windows as its foundation, benefits from global security updates but requires deeper IT expertise to secure the operating system properly.

Which architecture for which future?

The choice between these three giants depends on your industrial legacy and your technological ambitions:

Choose Rockwell if you operate in North America or if you need a standardized architecture that is easy to troubleshoot by technicians familiar with clear and powerful logic systems.

Choose Schneider Electric if your priority is energy transition, software openness, and the desire to deploy a decentralized and agile architecture based on IEC 61499.

Choose Beckhoff if you are pushing the limits of physics: extreme cycle rates, complex machine vision integration, or the need to merge high-level software code with industrial automation.

In the era of software-defined manufacturing, the boundary between these players is becoming thinner, but their architectural philosophies remain essential compasses for the engineers of tomorrow.

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These three manufacturers all have recognized expertise, but their approaches differ significantly. Robot architecture, industrial positioning, sector specialization, precision, speed, and operating environment: each player addresses specific needs.

So, how do you choose between ABB, Epson, and Stäubli depending on your production requirements? Robot Magazine offers a detailed analysis to help guide industrial decision-making.

Three leaders, three industrial philosophies

Before getting into the technical comparison, it is essential to understand the positioning of each manufacturer.

ABB: versatility and industrial power

Choosing an industrial robot
means making a strategic decision,
not just a technical one.

Epson: precision and speed for electronics and assembly

Epson has long been recognized for its SCARA robots and micro-assembly solutions, positioning itself as a key player in high-precision industrial automation. The company specializes in applications where very high precision, extremely fast cycle times, and maximum compactness are critical to performance.

This expertise translates into a strong presence across sectors such as electronics, component manufacturing, small-part assembly, and high-speed automated production lines, where efficiency, repeatability, and space optimization are essential.

Stäubli: high precision and critical environments

Stäubli takes a more niche yet highly demanding position within the robotics landscape. Its robots are renowned for their exceptional precision, long-term reliability, and ability to operate in sensitive environments where strict standards are required.

This level of performance makes them particularly well-suited for industries such as pharmaceuticals, medical applications, food processing, as well as clean or sterile environments and micromechanics, where accuracy, cleanliness, and consistency are critical.

Technical comparison: performance, precision, flexibility

1. Precision and repeatability

• Stäubli clearly stands out in this area. Its robots provide extremely fine repeatability, making them well suited for critical environments and high-precision applications.
• Epson also excels, especially with SCARA robots, where precision is essential for fast, repetitive operations.
• ABB offers high precision as well, but it is more focused on versatile industrial applications than on extreme micro-precision.

Verdict: Stäubli > Epson > ABB for very high-precision applications.

2. Execution speed

• Epson leads in short cycle times and high-speed production. Its SCARA robots are designed for rapid tasks with highly optimized cycle times.
• ABB delivers strong performance, but with a balance between speed and robustness.
• Stäubli prioritizes precision and stability over pure speed.

Verdict: Epson > ABB > Stäubli for very high-speed production lines.

3. Payload and power

• ABB offers a very broad range, including robots capable of handling heavy loads in demanding industrial environments.
• Stäubli covers intermediate payloads with high precision.
• Epson mainly focuses on light payloads.

Verdict: ABB > Stäubli > Epson for heavy-duty applications.

4. Operating environment

• Stäubli is the leader for clean, sterile, or sensitive environments such as cleanrooms, pharmaceuticals, and food processing.
• ABB is designed for standard to complex industrial environments.
• Epson is suitable for clean environments, but not as demanding as those typically targeted by Stäubli.

Verdict: Stäubli > Epson > ABB for critical environments.

5. Flexibility and integration

• ABB stands out for its ability to integrate complex systems, particularly through advanced software, simulation solutions, and connected architectures.
• Stäubli offers excellent integration within specialized systems.
• Epson focuses on simple, fast-to-deploy solutions, but these are less scalable in complex architectures.

Verdict: ABB > Stäubli > Epson for complex industrial systems.

Robotics is evolving toward
smarter, more adaptive
systems.

Choosing according to your type of production

Heavy production and full-scale industrial automation

If your production involves:

• Heavy handling
• Welding
• Palletizing
• Complex industrial lines

ABB is the natural choice.

Its versatility, robustness, and software ecosystem make it well suited for large-scale installations.

Fast assembly and electronics production

If you work in:

• Electronics
• Component assembly
• Very high-speed production lines

Epson is particularly suitable.

Its SCARA robots provide the speed and precision needed for short-cycle operations.

Critical production and sensitive environments

If your activity concerns:

• Pharmaceuticals
• Medical industries
• Food processing
• Clean environments

Stäubli is often the obvious choice.

Its precision and compliance with strict standards make it a benchmark player.

Cost, maintenance, and ROI

• The choice does not depend on technical performance alone. Total cost of ownership (TCO) is a key factor.
• ABB often involves a higher initial investment, but offers strong durability and scalability.
• Epson provides more accessible solutions, with fast ROI on high-speed lines.
• Stäubli positions itself in markets where quality matters more than cost, with return on investment driven by reliability and compliance.

2026 trends: toward a convergence of technologies

The differences between these players remain clear, but certain trends are bringing their approaches closer together:

• Growing integration of AI to improve flexibility
• Development of collaborative solutions
• Advancements in machine vision
• Use of digital twins for simulation
• Convergence between industrial robotics and intelligent robotics

Robots are becoming less rigid, more adaptive, and better able to handle increasing variability.

A strategic choice, not just a technical one

Choosing between ABB, Epson, and Stäubli is not about selecting “the best robot,” but identifying the one that best matches your industrial reality.

• ABB for power, versatility, and complex environments
• Epson for speed, precision, and fast assembly
• Stäubli for extreme reliability and critical environments

At a time when automation is becoming a strategic lever, the robot is no longer just a tool, but a central element of the production system.

The right choice is the one that fits into your value chain, your environment, and your long-term industrial vision.

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In recent years, this separation has begun to fade. By 2026, the convergence of robots and artificial intelligence is no longer limited to demonstrators or pilot projects; it is fundamentally redefining the very nature of the factory. This convergence signals a structural transformation of the industrial model, far beyond traditional automation.

From Rigid Automation to Contextual Autonomy

Traditional factories operated on a simple principle: production lines optimized for a specific product, with robots programmed for repetitive, predictable tasks. This model has reached its limits in the face of rising customization, market volatility, and labor pressures.

The integration of AI radically changes the game. Robots no longer just follow fixed trajectories; they begin to perceive, interpret, and adapt to their environment.

Cameras, force sensors, 3D vision, real-time analytics AI enables robots to handle part variations, logistical uncertainties, human interactions, or changes in production speed. The factory becomes less rigid, more responsive, and more tolerant of the unexpected.

The convergence of robots
and artificial intelligence does
not just modernize the factory
it redefines its very nature.

Emergence of the Robot as an Industrial Agent

A strong signal of the factory of the future is the changing status of the robot. It is no longer just an automated tool machine but an industrial agent with a degree of decision-making autonomy.

In practice, this means that a robot can:

• Adjust its actions based on context

• Detect anomalies or quality deviations

• Halt a process if it identifies a risk

• Cooperate with other robots or human operators

This evolution relies on specialized AI models capable of operating in constrained environments with high safety and reliability requirements. The intelligence is not general but targeted toward specific industrial applications.

A Factory Driven by Real-Time Data

The convergence of robots and AI also reveals a profound shift in industrial management. The factory of the future is not just automated; it is data-native.

Every robot becomes a data collection point: movements, forces, cycle times, quality, incidents, energy consumption. Continuously analyzed by AI systems, this data drives:

• Production flow optimization

• Predictive maintenance

• Energy management

• Continuous process improvement

The factory stops being a collection of isolated machines and becomes a living system capable of learning from its own operation.

From Programming to Industrial Reasoning

AI also changes how robots are designed and deployed. Whereas traditional programming required detailed, fixed instructions, modern approaches favor:

• Learning by demonstration

• Goal-oriented configuration

• Dynamic adaptation to constraints

Engineers no longer dictate every move but define frameworks, rules, and priorities. The robot then selects the best possible action within that framework. This approach reduces commissioning times and opens automation to tasks previously considered too complex or variable.

Human-Robot Collaboration as an Industrial Norm

The factory of the future, revealed by robot–AI convergence, is not human-free. On the contrary, it relies on structured collaboration between operators and intelligent machines.

Robots handle arduous, repetitive, or dangerous tasks, while humans focus on:

• Supervision

• Problem-solving

• Quality control

• Process improvement

• Strategic decision-making

AI plays a key role in securing interactions, anticipating behaviors, and adapting robots to human presence. The line between automation and collaboration becomes fluid.

Flexibility, Resilience, and Reshoring

The combination of robotics and AI also reflects a geopolitical transformation of industry. Factories of the future are designed to be more flexible and resilient.

Capable of quickly switching production, adapting to fluctuating volumes, and reducing dependence on scarce labor, they facilitate:

• Partial reshoring of certain production lines

• Securing supply chains

• Reducing industrial risks

Intelligent automation no longer focuses solely on productivity but on operational continuity in an unstable world.

Persistent Technological and Human Challenges

This vision of the factory of the future does not obscure the major challenges that remain. Robot–AI convergence raises complex issues:

• Industrial system cybersecurity

• Algorithm reliability in critical situations

• Accountability in case of incidents

• Social acceptance and job transformation

• Upskilling teams

AI introduces an element of non-determinism into environments historically designed for complete control. This requires new approaches to validation, certification, and industrial governance.

Industrial intelligence is not
general; it is specialized, constrained,
and purpose-driven.

A Gradual but Irreversible Transformation

Contrary to futuristic rhetoric, the factory of the future will not appear overnight. It is built in successive layers: smarter robots, more interconnected systems, better data-informed decisions.

But the direction is clear. The convergence of robots and AI does more than improve the existing system; it changes the very nature of the industrial system. Factory becomes adaptive, learning, and capable of absorbing uncertainty.

The Factory of the Future as a Collective Intelligent System

What robot–AI convergence reveals is not a fully automated or dehumanized factory, but a collective intelligent system in which machines, software, and humans cooperate in real time.

In this model, value is no longer measured solely by speed or production volume but by the ability to adapt, anticipate, and make responsible decisions.

The factory of the future will not be defined by the number of robots installed but by the quality of the intelligence orchestrating the system. On this front, the convergence of robotics and AI marks a major industrial turning point, whose effects are only beginning to be felt.

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In this article, Robot Magazine analyzes current applications, tangible benefits, and future prospects.

1. Smart production driven by data

Modern factories no longer rely solely on programmed machines but on systems capable of learning, anticipating, and responding. Thanks to the proliferation of sensors, connected industrial platforms, and machine learning models, production lines can now:

Automatically adjust their pace
Detect anomalies invisible to the human eye
Reduce scrap through continuous analysis
Optimize machine usage based on demand

Platforms like Azure AI, Google Cloud Manufacturing, and Nvidia Industrial Edge provide the computing power needed to analyze millions of data points per minute. According to McKinsey, these technologies can reduce unplanned downtime by 30% and improve quality by 10 to 20%.

2. Intelligent robots: a new generation of autonomous machines

The advent of AI is profoundly changing the role of industrial robots. They are no longer just programmed to repeat a movement but can understand and adapt their behavior to their environment.

Key advancements include:

Industrial vision enhanced by deep learning
Reinforcement learning
Robots capable of changing tasks without heavy reprogramming
Better human-machine interaction on the shop floor

Major players such as ABB, Fanuc, KUKA, Universal Robots, and Stäubli already deploy these features, while emerging players like Figure and Tesla Robot push robotic AI into new applications.

3. Predictive maintenance: anticipating failures before they occur

Predictive maintenance is one of the most mature uses of AI in industry. By continuously analyzing vibrations, temperatures, sounds, or pressures, algorithms can detect imperceptible variations that indicate a future failure.

The benefits are significant:

Reduced unplanned downtime
Better spare parts management
Optimized intervention scheduling
Extended equipment lifespan

Siemens, Schneider Electric, and PTC now offer integrated solutions combining IIoT sensors, AI, and digital twins.

4. The rise of dark factories: maximizing automation

The concept of the dark factory, a facility capable of running continuously with minimal human intervention, is no longer futuristic. In certain sectors—electronics, automotive, logistics—AI already enables highly advanced automation.

These factories rely on:

Autonomous robots
Fully automated quality inspection
Self-adaptive systems
Autonomous logistics flows

Far from eliminating humans, this model creates new roles: autonomous systems supervisor, industrial data technician, AI-robotics integrator, or industrial cybersecurity manager.

5. Quality inspection 4.0: AI’s eye for higher standards

AI-based industrial vision systems are revolutionizing quality inspection. Cameras paired with deep learning analyze thousands of images per minute and can detect micro-defects impossible for humans to identify.

The gains are substantial:

Reduced defects and customer returns
Enhanced traceability
Lower inspection costs
Improved compliance

Cognex, Keyence, Zebra, and Amazon Lookout for Vision are among the leaders driving this transformation.

6. Smart internal logistics: AI-driven AGVs and AMRs

Factory internal flows are also being transformed. AGVs (Automated Guided Vehicles) and AMRs (Autonomous Mobile Robots) navigate freely, optimize their routes, and adjust tasks in real time according to production load.

Benefits include:

Reduced unnecessary travel
Improved safety in the factory
Optimized storage and workflow
Lower intralogistics costs by 20 to 40%

These systems can now easily integrate with MES or industrial management software.

7. AI and energy: toward more efficient production

Rising energy costs are pushing manufacturers to adopt AI-based optimization solutions. These systems allow factories to:

Adjust consumption to peak pricing
Reduce energy losses
Better utilize renewable energy
Anticipate machine energy needs

Some factories report a 10 to 25% reduction in energy expenses thanks to AI.

8. Industrial AI agents: the next step toward autonomy

The next generation of industrial systems relies on AI agents. These models, capable of observing, analyzing, making decisions, and executing actions, represent a break from traditional automation.

They will be able to:

Supervise teams of robots
Reorganize a production line in real time
Manage internal orders
Autonomously optimize processes

These agents foreshadow fully autonomous factories.

A profound transformation, but still a human-centered industry

AI is not intended to replace operators but to reposition humans at the center of higher-value tasks. Employees become supervisors, analysts, programmers, and managers of complex systems.

Industry is entering a new phase of modernization where performance, sustainability, and flexibility meet. Artificial intelligence is no longer an optional tool; it is becoming a strategic pillar for the factories of the future.

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In a region with a strong industrial culture, Cetim’s presence takes on a particular significance: that of an organisation capable of making technologies often seen as “too complex” or “too futuristic” for SMEs more accessible, as highlighted by the testimony of Michael Grandidier, Operations Director at Fameca. The 2025 edition will therefore shine a spotlight on two innovations: a multi-sensor cobot cell dedicated to quality control, and IANote, an AI demonstrator capable of detecting anomalies in just a few seconds.

A Multi-Sensor Cobot Cell to Revolutionize Quality Control

The first solution presented by Cetim perfectly illustrates the rapid evolution of collaborative robotics in industry. It is a multi-sensor cobot cell designed to conduct feasibility studies for quality control under semi-industrial conditions.

Equipped with a latest-generation cobot, this cell can integrate various inspection technologies:

• material health monitoring,

• visual defect inspection,

• dimensional control,

• advanced non-destructive testing techniques,

• smart sensors and vision modules.

One of the major strengths of this demonstrator is its flexibility: manufacturers can combine several technologies, either successively or simultaneously, to identify the most relevant inspection solution for their parts and workflows.

Cetim will also present a real-world application on a welded mechanical assembly, showing how a collaborative robot can standardize and automate inspection tasks that are typically long and repetitive. The objective is clear: enhance repeatability, reduce human error, and allow operators to focus on higher-value tasks.

This cell aligns with the current evolution of French factories, where cobots no longer merely assist they optimize, secure, and enhance key processes.

IANote: An AI Demonstrator That Trains Its Models in 5 Seconds

The other innovation showcased at BE 5.0 will be presented as a premiere: the IANote demonstrator, an artificial intelligence solution dedicated to detecting anomalies on industrial parts.

While traditional systems require long and tedious training phases, IANote stands out thanks to an unprecedented capability:

ultra-fast training in just 5 seconds,
performed directly on defect-free parts,
requiring no prior database or expert configuration.

In practice, the AI instantly calibrates itself on a compliant part, then detects any surface, appearance or geometric anomaly in real time. This “zero defect, zero history” approach opens new possibilities, especially for production lines with short series or frequent product changes.

IANote reflects a major trend in industrial robotics: the rise of embedded AI fast, intuitive, field-ready, and operable directly by production teams, without the need for data scientists.

Circular Economy: Another Pillar of Industrial Transformation

Cetim’s booth will also highlight several achievements related to the circular economy a domain increasingly central to industrial strategies. Showcased items will include:

• eco-designed products,

• parts containing recycled materials,

• examples of retrofitted industrial equipment,

• demonstrators focused on extending lifespan.

These projects illustrate Cetim’s ability to support both technological modernization and the ecological transition of manufacturers.

A Conference on Connected Hydraulic Systems

One of the key highlights of the event will be a technical conference led by Nicolas Bedouin, an expert from Cetim, on Tuesday, November 25, from 10:45 to 11:15 AM (Jupiter room). The theme:

“Connected hydraulic units, IIoT and industrial monitoring.”

A topic that resonates with current industrial concerns: how to make hydraulic systems smarter, more predictive, and more energy-efficient through sensors and connectivity.

Quatrium Grand Est: An Acceleration Platform for Manufacturers

All showcased innovations come from Quatrium Grand Est, the acceleration platform located at KM0 in Mulhouse. This structure offers:

• personalized diagnostics,

• assistance in defining an action plan,

• support for selecting technical solutions,

• guidance through industrialization,

• a network of technological, financial, and training partners.

Manufacturers can test technologies on their own parts a key advantage for mitigating investment risks.

Cetim: More Central Than Ever to Industrial Transformation

With more than 1,100 experts, engineers, and PhDs, Cetim confirms at BE 5.0 its central role in modernizing French factories and integrating key technologies of the industry of the future: collaborative robotics, AI, smart sensors, monitoring, circular economy, and automation.

By focusing on concrete, testable, and rapidly deployable solutions, the institution positions itself as a strategic partner for a more efficient, sustainable, and competitive industry.

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Background & Strategy

With this announcement, Yamaha Motor strengthens its presence in the industrial automation market. Until now, its product lineup included single-axis robots, SCARA robots, and linear conveyor modules, but this cobot expands its portfolio toward even more flexible solutions.

Several factors explain this development:

• Industrial production is increasingly shifting toward shorter product life cycles, more varied product ranges, and smaller volumes (“high-mix, variable-volume” manufacturing).

• Demand for collaborative automation (robots working alongside humans) is rising sharply driven by labor shortages, increasing wage costs, and the growth of technologies such as IoT and electric mobility.

• Yamaha is targeting several sectors: automotive, home appliances, metalworking, as well as lighter industries like food, cosmetics, and textiles.

Main Features of the 7-Axis Yamaha Motor Cobot

7-axis configuration

Yamaha’s cobot is built on seven axes: three translational axes (X, Y, Z), three rotational axes (roll, pitch, yaw), plus a torsion axis equivalent to a human elbow. This architecture allows the arm to reach difficult areas, avoid obstacles, and adopt smoother and more natural trajectories.

• Maximum reach: 1,300 mm

• Payload capacity: up to 10 kg

Smooth motion thanks to torque sensors

Each axis is equipped with a high-precision torque sensor enabling compliance control: the robot dynamically adjusts its force depending on external contact.

• If it touches an operator, the cobot detects the impact and stops immediately, enhancing safety.

• It can handle delicate tasks such as inserting or removing connectors, polishing curved surfaces, and more.

Operating modes

• Collaborative mode (reduced speed): safe operation near humans.

• High-speed mode: for secure or fenced-off zones with appropriate protection.

The cobot is currently undergoing functional safety certification by TÜV SÜD, an independent third-party organization.

Accessible programming

In addition to traditional text-based programming, the cobot supports block programming: users assemble visual instruction blocks to create sequences, making programming intuitive even for beginners.

“Human-friendly” design

• Rounded arm with no sharp edges to minimize intimidation or discomfort.

• Matte finish (no shine) to give a warm, soft appearance and avoid the “scary industrial robot” look.

Dedicated controller & mobility

• The controller is highly compact, reducing control panel footprint.

• It includes a simple pendant (control interface) usable even without advanced expertise.

• 48 V DC input: allows the cobot to share the same battery as AGVs (Automated Guided Vehicles) or AMRs (Autonomous Mobile Robots).

Thanks to this compatibility, the cobot can be mounted directly on an AGV/AMR, combining mobility with automation.

Impact & Outlook

With this new product, Yamaha Motor strengthens its ability to deliver complete automation solutions (“total solutions”): robots, controllers, and automated transport.

By combining flexible cobots with AGVs/AMRs, Yamaha can offer more agile production architectures especially suited for modern factories with varied production lines, frequent changes, and strong human-machine interaction. By participating in events like iREX 2025, Yamaha signals a strong commitment to the future of smart factories, where mobile robotics and collaboration are at the core of production.

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